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Register a new userRadar Absorption, Basal Reflection, Thickness, and Polarization Measurements from the Ross Ice Shelf
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Radio-glaciological parameters from Moores Bay, in the Ross Ice Shelf, have been measured. The thickness of the ice shelf in Moores Bay was measured from reflection times of radio-frequency pulses propagating vertically through the shelf and reflecting from the ocean, and is found to be $576pm8$ m. Introducing a baseline of 543$pm$7 m between radio transmitter and receiver allowed the computation of the basal reflection coefficient, $R$, separately from englacial loss. The depth-averaged attenuation length of the ice column, $<L >$ is shown to depend linearly on frequency. The best fit (95% confidence level) is $<L( u) >= (460pm20)-(180pm40) u$ m (20 dB/km), for the frequencies $ u=$[0.100-0.850] GHz, assuming no reflection loss. The mean electric-field reflection coefficient is $sqrt{R}=0.82pm0.07$ (-1.7 dB reflection loss) across [0.100-0.850] GHz, and is used to correct the attenuation length. Finally, the reflected power rotated into the orthogonal antenna polarization is less than 5% below 0.400 GHz, compatible with air propagation. The results imply that Moores Bay serves as an appropriate medium for the ARIANNA high energy neutrino detector.
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The ARIANNA hexagonal radio array (HRA) is an experiment in its pilot phase designed to detect cosmogenic neutrinos of energies above 10^16 eV. The most neutrino-like background stems from the radio emission of air showers. This article reports on dedicated efforts of simulating and detecting the signals of cosmic rays. A description of the fully radio self-triggered data-set, the properties of the detected air shower signals in the frequency range of unit[100-500]{MHz} and the consequences for neutrino detection are given. 38 air shower signals are identified by their distinct waveform characteristics, are in good agreement with simulations and their signals provide evidence that neutrino-induced radio signals will be distinguishable with high efficiency in ARIANNA. The cosmic ray flux at a mean energy of $6.5^{+1.2}_{-1.0}times10^{17}$ eV is measured to be $1.1^{+1.0}_{-0.7}times10^{-16}$ eV$^{-1}$km$^{-2}$sr$^{-1}$yr$^{-1}$ and one five-fold coincident event is used to illustrate the capabilities of the ARIANNA detector to reconstruct arrival direction and energy of air showers.
In a previous paper, we presented an extension of our reflection model RELXILL_NK to include the finite thickness of the accretion disk following the prescription in Taylor & Reynolds (2018). In this paper, we apply our model to fit the 2013 simultaneous observations by NuSTAR and XMM-Newton of the supermassive black hole in MCG-06-30-15 and the 2019 NuSTAR observation of the Galactic black hole in EXO 1846-031. The high-quality data of these spectra had previously led to precise black hole spin measurements and very stringent constraints on possible deviations from the Kerr metric. We find that the disk thickness does not change previous spin results found with a model employing an infinitesimally thin disk, which confirms the robustness of spin measurements in high radiative efficiency disks, where the impact of disk thickness is minimal. Similar analysis on lower accretion rate systems will be an important test for measuring the effect of disk thickness on black hole spin measurements.
The polarization of the atmosphere has been a long-standing concern for ground-based experiments targeting cosmic microwave background (CMB) polarization. Ice crystals in upper tropospheric clouds scatter thermal radiation from the ground and produce a horizontally-polarized signal. We report the detailed analysis of the cloud signal using a ground-based CMB experiment, POLARBEAR, located at the Atacama desert in Chile and observing at 150 GHz. We observe horizontally-polarized temporal increases of low-frequency fluctuations (polarized bursts, hereafter) of $lesssim$0.1 K when clouds appear in a webcam monitoring the telescope and the sky. The hypothesis of no correlation between polarized bursts and clouds is rejected with $>$24$sigma$ statistical significance using three years of data. We consider many other possibilities including instrumental and environmental effects, and find no other reasons other than clouds that can explain the data better. We also discuss the impact of the cloud polarization on future ground-based CMB polarization experiments.
Many fast-flowing glaciers and ice streams move over beds consisting of reworked sediments and erosional products, commonly referred to as till. The complex interplay between ice, meltwater, and till at the subglacial bed connects several fundamental problems in glaciology including the debate about rapid mass loss from the ice sheets, the formation and evolution of subglacial landforms, and the storage and transport of subglacial water. In-situ measurements have probed the subglacial bed, but provide surprisingly variable and seemingly inconsistent evidence of the depth where deformation occurs, even at a given field site. These observations suggest that subglacial beds are inherently dynamic. The goal of this paper is to advance our understanding of the physical processes that contribute to the dynamics of subglacial beds as reflected in existing observations of basal deformation. We build on recent advances in modeling dense, granular flows to derive a new numerical model for water-saturated till. Our model demonstrates that changes in the force balance or temporal variations in water pressure can shift slip away from the ice-bed interface and far into the bed, causing episodes of significantly enhanced till transport because the entire till layer above the deep slip interface becomes mobilized. We compare our model results against observations of basal deformation from both mountain glacier and ice-stream settings in the past and present. We also present an analytical solution to assess the variability of till transport for different glacial settings and hydraulic properties.
The Austre Lovenbreen is a 4.6 km2 glacier on the Archipelago of Svalbard (79 degrees N) that has been surveyed over the last 47 years in order of monitoring in particular the glacier evolution and associated hydrological phenomena in the context of nowadays global warming. A three-week field survey over April 2010 allowed for the acquisition of a dense mesh of Ground-penetrating Radar (GPR) data with an average of 14683 points per km2 (67542 points total) on the glacier surface. The profiles were acquired using a Mala equipment with 100 MHz antennas, towed slowly enough to record on average every 0.3 m, a trace long enough to sound down to 189 m of ice. One profile was repeated with 50 MHz antenna to improve electromagnetic wave propagation depth in scattering media observed in the cirques closest to the slopes. The GPR was coupled to a GPS system to position traces. Each profile has been manually edited using standard GPR data processing including migration, to pick the reflection arrival time from the ice-bedrock interface. Snow cover was evaluated through 42 snow drilling measurements regularly spaced to cover all the glacier. These data were acquired at the time of the GPR survey and subsequently spatially interpolated using ordinary kriging. Using a snow velocity of 0.22 m/ns, the snow thickness was converted to electromagnetic wave travel-times and subtracted from the picked travel-times to the ice-bedrock interface. The resulting travel-times were converted to ice thickness using a velocity of 0.17 m/ns. The velocity uncertainty is discussed from a common mid-point profile analysis. A total of 67542 georeferenced data points with GPR-derived ice thicknesses, in addition to a glacier boundary line derived from satellite images taken during summer, were interpolated over the entire glacier surface using kriging with a 10 m grid size. Some uncertainty analysis were carried on and we calculated an averaged ice thickness of 76 m and a maximum depth of 164 m with a relative error of 11.9%. The volume of the glacier is derived as 0.3487$pm$0.041 km3. Finally a 10-m grid map of the bedrock topography was derived by subtracting the ice thicknesses from a dual-frequency GPS-derived digital elevation model of the surface. These two datasets are the first step for modelling thermal evolution of the glacier and its bedrock, as well as the main hydrological network.
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